Academic Journal

Instant Quality Control of Large Batch Processing Jobs.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Instant Quality Control of Large Batch Processing Jobs.
Συγγραφείς: Ahituv, Niv1, Zelek, Meir2
Πηγή: MIS Quarterly. Sep87, Vol. 11 Issue 3, p313-323. 11p. 6 Charts.
Θεματικοί όροι: *Quality control, *Computer operating systems, *Batch processing, *Manufacturing processes, *Process control systems, *Automatic control systems, *Statistics, *Quality assurance, *Mean time between failure, *Virtual storage (Computer science), Batch processing in electronic data processing, SADT (System analysis)
Περίληψη: The most common way to identify success or failure of a job running in a batch-processing mode is by examining a completion code sent by the job to the host operating system. Yet, for a variety of reasons the completion code may inaccurately indicate a successful termination of the job. This article describes a different approach to monitoring the quality of batch processing jobs while in operation. A pattern of behavior is suggested for a program. The pattern reflects ratios of consumption of various hardware resources. The ratios are determined by collecting historical performance variables of the job and analyzing the data by means of statistical methods. Once a pattern is set, the performance variables of every individual run of the program are compared with the precalculated pattern of behavior and if the deviation is beyond certain limits an alarm is triggered.
The proposed quality control technique has been tested on real applications, as well as on some artificial programs. The findings suggest that the technique is reliable in that it successfully distinguishes between proper and malfunctioning runs of a program. [ABSTRACT FROM AUTHOR]
Copyright of MIS Quarterly is the property of MIS Quarterly and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Business Source Index
Περιγραφή
ISSN:02767783
DOI:10.2307/248676